What does not work (well): Data Scientist Alice prototyped, say, a K-means model in Scikit-learn. After lots of parameter tuning and feature engineering, results looked great.

Because DataOps builds on DevOps, cross-functional teams that cut across “skill guilds” such as operations, software engineering, architecture and planning, product management, data analysis ...

Scoping the Problem. Before we dive into solutions, let’s lay out the problem in more detail. Scientists and engineers (data and otherwise) have always been like cats and dogs, oil and water.

Eppendorf SE and DataHow AG announce strategic collaboration to advance bioprocess data management. This partnership will integrate DataHow's innovative AI-enabled analytics solution, DataHowLab, with ...

The scientists believe that version control for cell engineering will make engineering biology more open, reproducible, easier to trace and share, and more trustworthy.

International collaboration key to science and engineering globalization. ScienceDaily . Retrieved April 2, 2025 from www.sciencedaily.com / releases / 2012 / 08 / 120831130859.htm ...

Despite all the relevant capabilities data scientists bring to the table, they are highly skilled, expensive, and not easy to find. The rate at which organizations are looking to implement and ...

Utilize computer science theories to create software that allows computers to meet the demands of an ever-changing, technologically-dependent society. Conduct research in many areas including data ...